At a Glance
- Tasks: Design and implement data solutions, manage infrastructure, and collaborate on AI projects.
- Company: Join UKRI, the UK's leading research and innovation funding agency.
- Benefits: Remote work, competitive pay, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make a real impact in cutting-edge AI and data engineering.
- Qualifications: Experience in data engineering, strong Python skills, and knowledge of AI technologies.
The predicted salary is between 50000 - 60000 £ per year.
On behalf of UKRI, we are looking for an AI Data Engineer (Inside IR35) for an initial 3 month contract, with potential to extend. Remote working with very occasional travel to Swindon.
UK Research and Innovation (UKRI) is the national funding agency investing in science and research in the UK. UKRI invests £8 billion of taxpayers' money each year into research and innovation and the people who make it happen. They work across a huge range of fields - from biodiversity conservation to quantum computing, and from space telescopes to innovative health care. They give everyone the opportunity to contribute and to benefit, bringing together people and organisations nationally and globally to create, develop and deploy new ideas and technologies.
The Data Engineer will be responsible for the requirements analysis and design of solutions for data platforms, ETL, integration and analysis solutions. Our toolset includes AWS hosted databases (Postgres, S3 based data lake, MySQL, Athena), integration services (AWS API gateway, lambda functions), ETL services (AWS Glue, Step functions, AWS Batch), infrastructure management tools such as Terraform and extensive use of SQL and Python.
As an AI Data Engineer your main responsibilities will be:
- Infrastructure Management: Set up and manage data infrastructure, including clusters, servers, and cloud-based resources using Terraform. Monitor and optimize system performance, troubleshoot issues, and ensure system availability.
- Data Architecture and Design: Design and implement scalable and efficient data pipelines, databases, and data warehouses. Collaborate with data visualization and analysts' teams to understand data requirements and translate them into technical specifications.
- Data Processing: Develop and maintain ETL (Extract, Transform, Load) processes for ingesting data from various sources into the data infrastructure. Optimize data processing and storage for performance and cost-effectiveness.
- AI: Build scalable inference pipelines and AI APIs. Implement MLOps workflows for model versioning, monitoring, and retraining. Collaborate with data scientists to productionize machine learning solutions. Evaluate and optimize AI model performance and operational efficiency.
- Database Management: Manage and maintain databases, ensuring data integrity, security, and availability. Implement database schema changes and optimizations as needed.
- Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to meet data requirements. Communicate effectively with stakeholders to gather requirements and provide updates on data engineering projects.
Essential:
- Comfortable working in an Agile rapidly changing environment.
- Data Engineering experience, with strong Python skills.
- Exposure, knowledge and/or experience of working with AI technologies.
- Experience with infrastructure deployment tools such as Terraform, CDK or cloud formation.
- Experience developing API based data integration.
- Excellent analytic skills associated with working on structured and unstructured datasets.
- Excellent SQL experience on various platforms (SQL, PostgreSQL, PL/SQL etc).
- Experience of several of MySQL, Oracle, SQL, Postgres, RDS, Aurora, Athena or other similar large scale database technologies.
Desirable:
- Experience working with AI frameworks such as LangChain/LlamaIndex.
- Experience with Vector databases (Pinecone, Weaviate, FAISS).
Please be aware that this role can only be worked within the UK and not Overseas.
Disability Confident: As a member of the Disability Confident Scheme, UKRI guarantees to interview all candidates who have a disability and who meet all the essential criteria for the vacancy. In cases where we have a high volume of candidates who have a disability who meet all the essential criteria, we will interview the best candidates from within that group. This scheme encourages candidates with a disability and/or neurodivergence to apply. In exceptional circumstances, we may also need to apply the desirable criteria in our shortlisting process which may include holding active security clearance.
In applying for this role, you acknowledge the following: this role falls in scope of the Off Payroll Working in the Public Sector legislation. Any rates of payment quoted will reflect the gross rate per day for the assignment and will be subject to appropriate taxes and statutory costs. As such the payment to the intermediary and your income resulting from this contract will be different.
AI Data Engineer employer: Alexander Mann Solutions - Public Sector Resourcing
UK Research and Innovation (UKRI) is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration across diverse fields. With a commitment to employee growth, UKRI provides opportunities for professional development while working on cutting-edge projects that impact science and research in the UK. The flexibility of remote working, combined with occasional travel to Swindon, allows for a balanced work-life experience, making it an attractive choice for those seeking meaningful and rewarding employment.
Contact Details:
Alexander Mann Solutions - Public Sector Resourcing Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines, ETL processes, or AI models. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with AWS, Terraform, and SQL. Practise common interview questions related to data engineering and AI to boost your confidence.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, it shows you're genuinely interested in working with us at StudySmarter, which can give you an edge in the hiring process.
We think you need these skills to ace AI Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Data Engineer role. Highlight your experience with Python, SQL, and any relevant AI technologies. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background makes you a great fit for the role. Keep it concise but impactful!
Showcase Your Projects:If you've worked on any relevant projects, whether personal or professional, make sure to mention them. We love seeing practical examples of your skills in action, especially with ETL processes and cloud technologies.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Alexander Mann Solutions - Public Sector Resourcing
✨Know Your Tech Stack
Familiarise yourself with the specific tools and technologies mentioned in the job description, like AWS services, Terraform, and SQL. Be ready to discuss your experience with these tools and how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled challenges in data engineering, especially in optimising ETL processes or managing databases. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Understand AI Integration
Since the role involves working with AI technologies, brush up on your knowledge of MLOps workflows and AI frameworks. Be prepared to discuss how you would collaborate with data scientists to implement machine learning solutions.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. You'll need to communicate with cross-functional teams, so being able to articulate your ideas clearly will set you apart during the interview.